1. Field of the Invention
The present invention relates generally to document services and, more particularly, to a system and method of searching and identifying documentation in a database comprised of solution-oriented information accessible by a search engine.
2. State of the Art
Computer systems have become increasingly beneficial in their application as tools for solving customer support issues in a wide variety of technical disciplines ranging from computer and peripheral operational debugging to operational customer support. With the complex nature of technology and the proliferation of complex systems and applications, there exists a need for improving database access mechanisms and the accuracy of the results returned by those mechanisms.
Prior to computerized technology proliferation, technology consumers or customers could obtain service by contacting specially trained individuals at customer service desks where they could explain the specific abnormal behavior of their equipment. Customers would present their problems to the customer service agents by describing the symptoms or equipment behavior they were experiencing. These “symptom-based” problem descriptions were then noted by a customer service agent and entered into a search engine that accessed a database searching for possible solutions.
Technology databases were and continue to be predominantly populated with “solution-based” entries that describe to a user or customer “how-to” perform an operation or repair on their technology. The terminology utilized in a solution-based database includes language specific to performing a function or operation rather than the operational anomaly terminology describing the technology behavior that would be exhibited and therefore perceived by the user. It is appreciated that database searches are more exhaustive and comprehensive if the search query more precisely matches the terminology utilized in the targeted database.
As such, customer service agents, using their vast experience and specialty training, would act as the transforming entity for converting the symptom-based problem described by a customer into a solution-based query for presenting to the database search engine. While such a manual approach presented modest improvements, search results were inconsistent due to the human subjectivity factor and interpretive nature of the process.
Furthermore, due to the reality that the vast majority of customer service database information is written in solution-based format, translation by the customer service agent, while generally resulting in modestly more precise search results, exhibited further shortcomings and additional advances were desirable. For example, the economics associated with customer service agents as well as the substantial deployment of systems requiring customer service quickly became overwhelming and the resulting quality of translation from symptom-based customer inputs to solution-based database queries became unmanageable.
Additional advances have occurred which allow customers to directly input their customer service issue in electronic form for processing by a search engine in order to retrieve solutions to symptoms from the database. Unfortunately, customers present their issues to the search engine not only in the less compatible “symptom-based” form but also in “natural language” form which requires parsing of the words in order to extract the suitable search terms for inputting into a search engine. Natural language parsing is well known in the art and has met with marginal success when applied to a customer service application as they still engage in searching a database that is not based on the same syntax style or terminology of the input query.
The substantiality of the technological proliferation and the expanse of the customer base dictates that customers must directly access databases, such as customer service databases. Since customers are of diverse competencies and untrained to the nuances of the myriad of database syntaxes, as well as the fact that customer-generated queries are subject to the subjective stylization of the customer, an automated and mechanized approach is desirable.